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Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals

Radu Horaud 1 Matti Niskanen 1 Guillaume Dewaele 2 Edmond Boyer 1 
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : We address the problem of human motion tracking by registering a surface to 3-D data. We propose a method that iteratively computes two things: Maximum likelihood estimates for both the kinematic and free-motion parameters of a kinematic human-body representation, as well as probabilities that the data are assigned either to a body part, or to an outlier cluster. We introduce a new metric between observed points and normals on one side, and a parameterized surface on the other side, the latter being defined as a blending over a set of ellipsoids. We claim that this metric is well suited when one deals with either visual-hull or visual-shape observations. We illustrate the method by tracking human motions using sparse visual-shape data (3-D surface points and normals) gathered from imperfect silhouettes.
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Submitted on : Wednesday, January 13, 2010 - 4:05:17 PM
Last modification on : Wednesday, May 4, 2022 - 9:56:03 AM
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Radu Horaud, Matti Niskanen, Guillaume Dewaele, Edmond Boyer. Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31 (1), pp.158-163. ⟨10.1109/TPAMI.2008.108⟩. ⟨inria-00446898⟩



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